/**
 * Copyright 2020-2021 Huawei Technologies Co., Ltd
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

#ifndef MINDSPORE_LITE_SRC_PASS_FUSION_BN_TO_SCALE_FUSION_H_
#define MINDSPORE_LITE_SRC_PASS_FUSION_BN_TO_SCALE_FUSION_H_

#include <vector>
#include "backend/optimizer/common/optimizer.h"

namespace mindspore::opt {
class BatchNormToScaleFusion : public Pass {
 public:
  BatchNormToScaleFusion() : Pass("BatchNormToScaleFusion") {}
  ~BatchNormToScaleFusion() override = default;
  bool Run(const FuncGraphPtr &func_graph) override;

 private:
  bool CheckBNCanFused(const AnfNodePtr &node);

 private:
  std::vector<int64_t> input_shape_;
};

int CalculateScaleAndBiasFromBN(const CNodePtr &bn_node, int kernel_num, float *trans_scale, float *trans_bias);
}  // namespace mindspore::opt
#endif  // MINDSPORE_LITE_SRC_PASS_FUSION_BN_TO_SCALE_FUSION_H_
